1. Field of the Invention
The present invention relates to using computing devices to determine the number of people in a crowd. More particularly, the present invention relates to using visual hull information in order to determine the number of people in a crowd.
2. Description of Background Art
Several techniques exist for determining the number of people in a crowd. However, each of these techniques has its drawbacks. One technique is to generate an aerial image of a crowd and then count the number of people in the image. For example, a crowd at an outdoor venue can be photographed from an airplane or satellite. This image can then be used to count the number of people in the crowd. One disadvantage of this technique is that in order to obtain such an image, the crowd must be outdoors. Another disadvantage is that the image is often of poor resolution, making it difficult to count the number of people. Yet another disadvantage is that this technique provides the number of people in a crowd at a specific point in time (i.e., when the image was produced). In order to determine, at a later time, the number of people in the crowd, the entire process must be duplicated. This is because there is no way to use information obtained in the first iteration during the second iteration.
Another technique, which takes into account the dynamic nature of a crowd, is to designate physical checkpoints within and/or around the crowd. The number of people in the crowd is then estimated based on the number of people that pass by the checkpoints. The number of checkpoints required depends on the size of the crowd, and several checkpoints are often necessary. One way to determine the number of people at a checkpoint is manually (i.e., a person actually counts the people). This technique is very labor-intensive. Another, less labor-intensive, way is to use devices to count people. For example, a camera can “watch” a crowd at a checkpoint and a computer can process the resulting image. Both of these techniques are error-prone when checkpoints are busy, however, because people tend to occlude each other, making it difficult to determine how many people are present.
Another problem with the checkpoint technique is that of double counting. It's possible for a person to be visible from multiple checkpoints. This may occur because the person has moved between the checkpoints or because the viewing areas of the checkpoints overlap. The first situation can be addressed by determining, roughly simultaneously, how many people are at each checkpoint. The degree of simultaneity necessary depends on the mobility of people in the crowd and the distance between checkpoints. The second situation, however, still remains. An alternative approach is to identify (track) specific individuals and then ensure that each individual is counted only once. Tracking individuals is difficult when imaging devices are used to count people at a checkpoint. First, individuals can look very similar. Additionally, information from several different devices must be aggregated and processed, which requires a lot of bandwidth and computation.
What is needed is a way to determine the number of people in a crowd in real time using a limited amount of bandwidth and a limited amount of computation, regardless of the size and density of the crowd.